NotebookLM Podcast Automator

Automate Google NotebookLM with a small FastAPI service and Playwright. Upload sources (URLs, YouTube videos, or raw text), generate Audio Overviews, and retrieve the finished files programmatically—no manual clicking through the UI.

Key Features

• Upload multiple source types (URL, YouTube, text) into a notebook via REST.
• Trigger Audio Overview generation with optional style and prompt overrides.
• Track generation status and fetch download URLs or the binary audio file.
• Handles English and Hebrew NotebookLM interfaces automatically.
• Can auto-launch Chrome with a dedicated profile or attach to an existing debug session.

Architecture At A Glance

• FastAPI app (notebooklm_automator.api.app) exposes REST endpoints in api/routes.py.
• NotebookLMAutomator (core/automator.py) orchestrates Playwright, manages language detection, and delegates to feature managers.
• Browser control (core/browser.py) handles Chrome remote-debugging and profile management.
• Sources & audio managers (core/sources.py, core/audio.py) interact with the NotebookLM UI to add sources, generate audio, and fetch downloads.
• Selectors (core/selectors.py) provide localized UI selectors for supported languages.

Prerequisites

• Python 3.9+
• Google Chrome or Chromium with remote debugging enabled
• A NotebookLM account and an existing notebook URL
• uv (optional but recommended for reproducible installs)

Installation

From the repository root:

Using uv (recommended)

uv sync
uv run playwright install chromium

Using pip

pip install -e .
playwright install chromium

Running Locally

1. Create a .env file or export the notebook URL:
   • NOTEBOOKLM_URL="https://notebooklm.google.com/notebook/<YOUR_ID>"
2. First run: the service will open a Chrome profile at ~/.notebooklm-chrome. Log in to your Google account in that window so the session persists.
3. Start the API:

   uv run run-server
   # or override via CLI
   uv run run-server --notebook-url "https://notebooklm.google.com/notebook/<YOUR_ID>"
   

The API serves at http://localhost:8000 with Swagger UI at /docs.

Docker

docker build -t notebooklm-podcast-automator .
docker run -p 8080:8080 -e NOTEBOOKLM_URL="https://notebooklm.google.com/notebook/<YOUR_ID>" notebooklm-podcast-automator

Configuration

All values can come from environment variables or .env:

Manual Chrome launch (if you set NOTEBOOKLM_AUTO_LAUNCH_CHROME=0):

# macOS
/Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome \
  --remote-debugging-port=9222 \
  --user-data-dir="$HOME/.notebooklm-chrome"

# Windows (PowerShell)
& "C:\Program Files\Google\Chrome\Application\chrome.exe" `
  --remote-debugging-port=9222 `
  --user-data-dir="$env:USERPROFILE\.notebooklm-chrome"

# Linux
google-chrome --remote-debugging-port=9222 --user-data-dir="$HOME/.notebooklm-chrome"

Common Pitfalls & Troubleshooting

• Not logged in: Ensure the Chrome profile (NOTEBOOKLM_CHROME_USER_DATA_DIR) is signed into your Google account before calling the API.
• Port already in use: Change NOTEBOOKLM_CHROME_PORT (and matching manual Chrome launch) if another process is using 9222.
• Download failures: The API sanitizes filenames, but Chrome still needs download permission in the profile directory. Clear blocked downloads and retry.
• Tests endpoint: The /run-tests route expects local test files. This repository snapshot does not include the test suite; add your own tests before invoking it.

Future Improvements

• Re-introduce and publish the automated test suite with CI coverage.
• Add health checks for Chrome connectivity and clearer API error payloads.
• Ship a published container image for easier deployment.

License

MIT license. See LICENSE for details.